Successfully perceiving and recognizing the actions of others is of utmost importance for the survival of many species. For humans, action perception is considered to support important higher order social skills, such as communication, intention understanding and empathy, some of which may be uniquely human. Over the last two decades, neurophysiological and neuroimaging studies in primates have identified a network of brain regions in occipito-temporal, parietal and premotor cortex that are associated with perception of actions, also known as the Action Observation Network. Despite growing body of literature, the functional properties and connectivity patterns of this network remain largely unknown.

The goal of this dissertation is to address these general questions about functional properties and connectivity patterns with a specific focus on whether this system shows specificity for biological agents. To this end, we collaborated with a robotics lab, and manipulated the humanlikeness of agents that perform recognizable actions by varying visual appearance and movement kinematics. We then used a range of measurement modalities including cortical EEG oscillations, event-related brain potentials (ERPs), and fMRI together with a range of analytical techniques including pattern classification, representational similarity analysis (RSA), and dynamical causal modeling (DCM) to study the functional properties, temporal dynamics, and connectivity patterns of the Action Observation Network.

While our findings shed light on whether the human brain shows specificity for biological agents, the interdisciplinary work with robotics also allowed us to address questions regarding human factors in artificial agent design in social robotics and human-robot interaction such as uncanny valley, which is concerned with what kind of robots we should design so that humans can easily accept them as social partners.

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Tool use is a hallmark of the human species and an essential aspect of daily life. Tools serve to functionally extend the body, allowing the user to overcome physical limitations and interact with the environment in previously impossible ways. Tool-body interactions lead to significant modulation in the user’s representations of body size, a phenomenon known as tool embodiment. In the present dissertation, I used psychophysics and event-related brain potentials to investigate several aspects of tool embodiment that are otherwise poorly understood.

First, we investigated the sensory boundary conditions of tool embodiment, specifically the role of visual feedback during tool use. In several studies, we demonstrate that visual feedback of tool use is a critical driver of tool embodiment. In one such study, we find that participants can embody a visual illusion of tool use, suggesting that visual feedback may be sufficient for tool-induced plasticity.

Second, we investigated the level of representation modulated by tool use. Is embodiment confined to sensorimotor body representations, as several researchers have claimed, or can it extend to levels of self-representation (often called the body image)? Utilizing well-established psychophysical tasks, we found that using a tool modulated the body image in a similar manner as sensorimotor representations. This finding suggesting that similar embodiment mechanisms are involved at multiple levels of body representation.

Third, we used event-related brain potentials to investigate the electrophysiological correlates of tool embodiment. Several studies with tool-trained macaques have implicated multisensory stages of somatosensory processing in embodiment. Whether the same is true for humans is unknown. Consistent with what is found in macaques, we found that using a tool modulates an ERP component (the P100) thought to index the multisensory representation of the body.

The work presented in this dissertation advances our understanding of tool embodiment, both at the behavioral and neural level, and opens up novel avenues of research.

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